Growing smarter: a systematic review of the impact and challenges of climate information on farming

There is a great deal of unpredictability surrounding agricultural production, most of which comes from daily weather variations and seasonal variations caused by climate variability (Thomas & Nanteza 2023). Theoretically, improved weather and climate forecasts should enhance farmers' economic well-being by either higher revenue or less fluctuation. Combining sectoral decision models with advanced seasonal climate forecast skills might allow decision-makers to reduce or benefit from needless losses (Zhang et al. 2020). As climate change increases the unpredictability and uncertainty of weather and climate patterns, forecasts should become more beneficial to producers. Much research indicates that increasingly complex and precise weather and climate forecasts may be valuable for uses like agricultural output (Bacci et al. 2020). The agricultural sector can lessen weather and climate impacts using decision support tools, climate information, and weather forecasts (Lu et al. 2021). These weather resources must, however, be created and made available in a way that encourages farmers to use them to support agricultural decision-making. Availability and accessibility of CIS are crucial to ensuring that the agriculture sector is climate-resilient and has access to relevant and useable climate information (Djido et al. 2021). Several stakeholders are working to create and advance climate services that help farmers make adaptive farming decisions (Vincent et al. 2018). Nothing has changed significantly regarding providing farmers with relevant climate information (Tall et al. 2018).

Furthermore, users' perceptions facilitate the identification of barriers to using meteorological data across various user qualities and are underrepresented in agricultural decision-making. Multiple studies also demonstrate that understanding users' perspectives facilitates understanding the factors that encourage and impede climate forecast adoption and uptake, such as scarce resources and unpredictability in climate projections (Muita et al. 2021). Weather forecasters are assumed to be able to create goods and services without consulting consumers or their wants and perceptions (Porter & Dessai 2017). However, producers of climate forecasts assume that users will find the information practical and helpful. Suppose institutional support, dissemination, and communication strategies are implemented. In that case, the user-driven approach can successfully translate to information usability while offering a climate forecast personalized to the users' wants and needs, which may alleviate some of the problems noted. It is useful when a forecast meets a user's timeliness, accuracy, spatial- and time-resolution requirements, and other user-sensitive features (Ceglar & Toreti 2021). However, this will only be feasible if we produce climate forecasts which involve bringing the user on board through a multidisciplinary and participative approach and changing CIS from producer-oriented to user-focused (Porter & Dessai 2017).

Feedback from the forecast performance review is crucial for ‘service providers’ and ‘end users,’ or farmers. The quality of agronomic advisories, weather and climate forecasts, and their distribution and adoption by farmers are all considered in the evaluation of forecasts (Vogel et al. 2017). How farmers use the knowledge to adjust their practices (for example, a forecast of heavy rain influences their decision to apply fertilizer or a forecast of a dry spell influences their decision to sow crops). Information about extreme weather events, seasonal climate patterns, and daily weather conditions must be presented in a way that makes sense for decision-making (Singh et al. 2018). Information on the weather and climate is also relevant to socio-cultural contexts, economic development, and variations in vulnerability levels (Adger et al. 2003). Decision-makers can develop and enhance their farming management skills by thoroughly understanding CIS's application and format (Hansen & Sato 2004). Three factors are highlighted by Cash et al. (2006) as ways to innovate the CIS: first, the farmer's perspective on the context of choice; second, the various drivers; and third, the way the farmers translate the climatic information into action. The evaluation examines the issue, ‘What are the determinants of decision-making?’ to assess the forecast performance in farmers' decision-making. To clarify this, we posed four additional queries:

• (1) How do farmers and their farms' features affect decisions?

• (2) In what manner is the forecast presented to a farmer?

• (3) What are the farmers' anticipated ‘value’?

• (4) How has CIS unfolded into adaptation practices, including adjustments for both long-term climate changes and extreme weather events?

We obtained 845 articles using the Scopus search (Abstract and Title), 615 papers from the EBSCO discovery service under the ‘Title’ category, and 182 papers under the ‘Abstract’ category. A total of 503 articles in the Title and 157 papers in the Abstract were kept after the paper was repeatedly searched on the EBSCO Discovery Service and removed. A total of 663 were found in Scopus, with an additional 44 in the Abstract and 94 in the Title via an EBSCO discovery service search based on the article's Abstract. The publications that appeared in both Scopus and EBSCO Discovery Service that overlapped were eliminated, leaving 114 titles and 14 abstracts in EBSCO Discovery Service. For the review, the articles that satisfied the inclusion requirements were downloaded for 112 papers (60 from Scopus, 46 (from Title), and 6 (from abstract) from EBSCO Discovery Service).

Results show that most studies addressing farmers' responses to climate change were released after 2010. Out of the 112 studies, nearly 70% were published after 2015 and 30% before 2014. A growing trend of studies focusing on the change in the decision-making of African countries and farmers is seen in 20% of the publications published in the last two years (Figure S3, Supplementary Material). While a specific cause for this increase cannot be determined with certainty, one of the main theories is that the developed world's 2009 commitment to climate finance increased interest in climate adaptation among developed countries.

The evaluated studies showcased a variety of adaptation tactics in sub-Saharan Africa, primarily from farmers in eastern Africa (45.52%), western Africa (38.21%), and southern Africa (17.79%), concerning the geographic scope covered and followed by developed countries (15.20%) such as the USA and Australia and Asian countries (10.50%) such as India and Pakistan (Figure S4, Supplementary Material). Every study concentrates on a single nation, except for one that is presented as a ‘multi-country’ paper and includes numerous nations, namely Ghana, Burkina Faso, Mali, Senegal, and Niger (western Africa) and Kenya, Ethiopia, Tanzania, and Uganda (eastern Africa).

The study employs decision-theory-based methodological techniques to leverage the advantages of CIS. A total of six studies reveal the value of forecasting based on cost/loss. According to research, accurate forecasting reduces losses, while inaccurate forecasting increases input costs (Balbi et al. 2013). Additionally, real-time information and forecasting have been shown in two studies to improve net returns (Maini & Rathore 2011). A total of eight studies have examined farmers' willingness to pay. The evaluation bases the anticipated value on willingness to pay and economic gain. In the review, we concentrate on the farmers' primary decision-making objectives: maximize yield and production while lowering input costs. Financial gain farmers experience from implementing the forecast can be used to calculate the forecast's value. Four sections comprise the forecast's value and its economic impact:

• 1. Economic value: Out of the 112 studies, ten studies calculated the annual benefit and economic worth of the climate forecast. Studies use simulation and the contingent valuation method to assess the economic benefit of seasonal climate forecasts and ENSO (El Niño–Southern Oscillation) phases. The yearly advantage of forecasts such as seasonal climate forecasts and ENSO was estimated in the studies to determine the economic value (Amegnaglo et al. 2017). The study indicates that early warning systems and seasonal forecasts help decide cropping patterns, plant area expansion, and gross margin growth (An-Vo et al. 2019).

• 2. Comparative analysis: A total of five out of the 112 studies examined farmers who attain greater financial outcomes compared with farmers or advisors who do not incorporate climate information (Bert et al. 2007). In four studies, farmers who use forecasts and advisory experiences have higher yields than those who do not (Maini & Rathore 2011). Studies also elicit poor forecast impacts on their income (Balbi et al. 2013). On the contrary, other studies also show that forecasting increases revenue and yield while reducing losses (Moreto et al. 2021). Seasonal forecasting, for instance, assists farmers in choosing a wider variety of crops, raising average agricultural income (Gunda et al. 2017).

• 3. Economic benefit depends on the type of year and availability of forecast at different stages of crop growth: A total of six studies out of the 112 studies stressed that while a farmer's revenue is predicted to fluctuate depending on the type of year, this is still a factor in the income (Roudier et al. 2012). There will be a financial benefit if the forecast rainfall exceeds normal (Phillips et al. 2002). However, the forecast also aids in lowering losses during difficult years. The availability of forecasts at various stages of the crop growth season and the method of production (irrigated versus rainfed) affect the crop yield response based on forecasts (Adams et al. 2003).

• 4. Short- and medium-range forecasts have more economic value: Out of the 112 studies, in six, medium- and short-term forecasts provide more excellent economic value for farmers. For example, ten-day predictions on their own or in conjunction with seasonal forecasts are advantageous for all kinds of farmers (Singh & Borah 2013; Roudier et al. 2016; Haigh et al. 2018). In drought years, a seven-day forecast can save irrigation water and boost agricultural productivity (Cai et al. 2011).

Of the 112 studies, eight referred to farmers' willingness to pay. Out of the eight studies, seven involve farmers who are prepared to pay, and one involves farmers who are willing to get the information without charge but are not ready to pay (Maini & Rathore 2011). A total of three out of the eight studies indicate the percentage of farmers willing to pay; the range is a minimum of 17% (Haigh et al. 2018) to a maximum of 99% (Ali et al. 2020). In four studies, farmers are willing to pay for seasonal forecasts and agrometeorological alerts. One study listed the kinds of data farmers prepared to pay for and the justifications they provided for not wanting to pay. According to Ouédraogo et al. (2018), 39% of respondents are willing to pay for agro-advisories, 33% for decadal climate information, and 53% are willing to pay for daily weather and seasonal climate forecasts. Due to financial constraints, 28% of farmers are unwilling to pay, and 11% require proof of the benefits of using CIS. Farmers are more willing to foot the bill for participatory decision-making (Tesfaye et al. 2019). Nevertheless, only two studies were noted that computed the combined WTP (willingness to pay) of farmers and the minimum average yearly economic value (Figure S9, Supplementary Material).

To elicit the format, we analyze the frequency, range, and type of climate forecast farmers received from CIS.

• 1. Frequency of climate forecast issuance: As previously stated, lead time is the time between the forecast's release and the anticipated phenomena's occurrence (Ogutu et al. 2018). The forecast's strength is determined by how frequently it is released. There are four possible forecast frequencies: daily, weekly, monthly, and decadal. Most studies release their forecasts monthly (58) and daily (47). These are followed by studies that release their forecasts on a weekly and monthly (eight studies), daily and monthly (eight studies), weekly (six studies), twice weekly (six studies), and decadal (four studies) basis. The frequency of climate forecast issuance varies as follows: one study indicated that forecasts are released with different lead times including daily and weekly forecasts; seasonal forecasts for one to three months; and decadal forecasts. Additionally, forecasts are available monthly; weekly; daily; and seasonally (Figure S6, Supplementary Material).

• 2. Range of climate forecast released: Kaur & Singh (2019) stated that forecasts can be made for a variety of periods, including current casting (a few hours to a day), short-range (1–3 days), medium-range (3–10 days), and long-range (months or seasons) (Vedeld et al. 2020). Most of the research (39 studies) communicates a seasonal forecast to farmers, which is followed by long-term (23 studies), medium-term (21 studies), and short-term (six studies), respectively. A total of 11 studies do not mention the type of forecast, while studies have disseminated short- and long-term, medium- and seasonal forecasts. One study discusses various types of climate forecasts, including, seasonal, long-term, short-term, and medium-term forecasts (Figure S7, Supplementary Material).

• 3. Types of climate forecast released: Data and evidence demonstrating how farmers' decisions have changed in response to climate information are rising. Seasonal climate forecasts are given in 83 studies out of the 112 studies; agrometeorological forecasts are distributed in 12 studies out of the 112 studies; and climate and weather forecasts in 37 studies (Figure S8, Supplementary Material).

Agroclimatic advisories are experts giving farmers recommendations regarding using alternatives and tactics based on the forecast (Diouf et al. 2019). If farmers cannot use the forecast, its availability does not ensure they will make money (Hu et al. 2006). Farmers reported receiving forecasts with advice and recommendations in 55 studies, and in 63 studies forecast information was provided (Figure S9, Supplementary Material). Out of the 55 studies, 47 studies demonstrate that farmers were provided with and still require advice and recommendations. A total of six studies out of the 47 studies stressed the need for or provision of pesticides and fertilizer application and advised farmers to prevent pest and disease outbreaks (Chattopadhyay et al. 2018). It is also thought to be crucial to follow recommendations for irrigation and seed variety (Sifundza et al. 2019). A total of three studies of the 55 studies (Lin et al. 2019) demonstrate the expected value of advising. Out of 55 studies, five have a negative connotation associated with their agrometeorological advisories and recommendations. Out of the five studies, two emphasize farmers' autonomy and decision-making skills more than they do the offering of advice (Dayamba et al. 2018). The study focuses on the underutilization of climate service recommendations and their inability to assist smallholder farmers (Vedeld et al. 2020). However, in one study, marketing and agricultural advice precede climate service information (Haigh et al. 2018).

Farmers make decisions based on various factors, including farm features like size and resource availability and farmer attributes such as age, gender, education, resources, and attitude.

• 1. Age: Age is considered a significant determinant that influences the usability of climatic information in about 17 out of the 112 studies. Studies highlight that growing older makes one more susceptible to harsh weather disasters. According to studies, farmers of age 44 and older are potential CIS users (Walker 2021). The interactive method of getting climate services, such as extension agents, was preferred by the elderly population (Tesfaye et al. 2019). On the other hand, older people benefit others through their experience and understanding of climatic information (Kolawole et al. 2014).

• 2. Gender: Out of the 112 research studies, 16 studies present a gender perspective on using climate information. Studies that examine how people use climate information through a gender lens vary. According to several studies, men and women approach obtaining climate information and making decisions differently (Nyasimi et al. 2017). Studies have shown that households headed by men are more likely to receive information and make decisions about farming (Maggio & Sitko 2019). Men and women also have different preferences when it comes to information channels. According to Dayamba et al. (2018) and Henriksson et al. (2021), women prefer a knowledge broker to discuss and evaluate the information.

• In contrast, males are more likely to get forecasts from channels like the Internet, WhatsApp, SMS, or newspapers. Research has also shown that women's access to information is impeded by a high rate of illiteracy and the workload associated with domestic duties (Nyantakyi-Frimpong 2019). However, according to other studies, the availability of climate information causes men and women to behave differently (Walker 2021).

• 3. Education: Out of the 112 studies, 13 demonstrate education's importance in helping people understand climate change information. Research indicates that farmers with formal education are more willing to use climate services than farmers without education (Ebhuoma et al. 2020). Studies elicit that farmers with higher levels of education are also more likely to use information and communication technology (ICT) platforms such as smartphones and the Internet, cell phones, computers, video conferencing, social networking, and other media applications and services that enable users to access, retrieve, and transmit information (Henriksson et al. 2021). However, less educated farmers are less accepting of the latest climate services technology and are more vulnerable to the adverse effects of climate change. Studies have shown that education, financial aid, and awareness can reduce smallholder farmers' vulnerability to drought under climate change (Lemos et al. 2002). Studies also emphasize how education plays a role in decision-making, such as choosing seed variety (Ouédraogo et al. 2018). The ability of knowledgeable farmers to adjust to new technologies and make better decisions also increases their revenue (Gunda et al. 2017).

• 4. Availability of resources: A total of seven studies out of the 112 studies show that because they have less access to climatic information, farmers with fewer resources are more vulnerable to climate change (Lemos et al. 2002). Their susceptibility to climatic abnormalities is increased by poverty, marginalization, and a restricted resource base (Furman et al. 2014). Framers cannot obtain and use climate information due to insufficient resources and agricultural technologies (Ingram et al. 2002).

• 5. Farm size: Out of the 112 research studies, three consider farm size a determining factor in using climatic information. Due to increased diversification, large farms are less likely to adopt climate knowledge (Amegnaglo et al. 2017). Farmers who own big farms tend to prioritize non-farm activities over advisories and risk management (Tesfaye et al. 2019).

• 6. Farmer's attitude and understanding: Out of the 112 research studies, five studies demonstrate how a farmer's mindset influences an agro-economic decision. Research indicates that key factors in farmers' decision-making have included controllability (reliability, timeliness, availability, and accuracy of weather and climate information), self-efficacy (farmer ability and understanding), subjective construction of social and personal identities, goals, and values, and cultural contexts and understanding (Roncoli et al. 2016).

These articles fall into three topics because of their broad applicability to the current topic: (i) documenting adjustments made on farms, (ii) adaptation options and CIS application, and (iii) challenges of adaptations (Figure S11, Supplementary Material).

• (i) Documenting adjustments made on farms: In 75 studies, out of the 112 studies that reported on farmers' adjustments on the farm, roughly 33 studies published on farmers' adaptations did not describe the adaptation tactics farmers use on their farms. The five main topics under which these adaptation strategies fall are crop management (Tesfaye et al. 2019), water management (Nyasimi et al. 2017), fertilizer management (Andersson et al. 2020), land management (Henriksson et al. 2021) and a few on technological management (Camacho & Conover 2019) and financial management (Tesfaye et al. 2020).

• (ii) Adaptation options and CIS application: Among a wide range of adaptation actions undertaken by farmers, the most likely used strategies would be change of planting date (88.2%), change of crop acreage (61%), change of crop variety (56.9%), change of crops planted (52.8%) and increase of fertilizer (41.9%) crop allocation. It is common for farmers to modify their management strategies tactically based on information they deem pertinent to the future crop's prospects (Ouédraogo et al. 2018). Adapting forecasting to agricultural investment, crop selection, and scheduling of farm operations benefits farmers (Eakin 2000). CIS is essential for lowering crop failure rates, raising farm output, and guaranteeing effective resource utilization in agroecosystems. Application is based on short-term weather predictions, while choices about crops to plant, irrigation system configuration, and timing of irrigation are based on seasonal precipitation estimates (Vogel et al. 2017)

More than 42% of farmers modified their crops and preferred it above expanding the area for drought-resistant farming, altering planting dates, planting later than usual, modifying pest-control techniques, and adding more fertilizer. Decision-making was aided by the greater availability of early warning systems, predictions, and guidance on drought resilience; over 70% of farmers made decisions sooner than usual (Ewbank et al. 2019).

The effects of rising temperatures and changing rainfall patterns brought on by climate change can be lessened by irrigation. According to farmers, accurate and timely weather-based agro-advisory communications assisted them in making well-informed decisions regarding the usage of inputs, which resulted in savings on irrigation and lower costs for other inputs like fertilizer and pesticides (Mittal 2016). Most of the research under this theme focused on regions where rice, wheat, maize, fruits, and vegetables are farmed. However, they talked about the adaptation tactics for a single crop or a combination of crops rather than finding adaptation approaches particular to each crop. In addition, most of this research addressed adaptation, but ‘the question is adaptation to which condition?’ by focusing on climate change and climate variability. Only a few studies focused on specific risks, conditions, and vulnerabilities in which certain adaptation measures were adopted.

• (iii) Challenges of adaptations: Despite the seasonal climate forecast's indication of dry conditions, a far smaller percentage of farmers carried out their planned planting of drought-tolerant seeds. Because they cannot be stored and are more expensive than native seeds, drought-tolerant seeds must be bought yearly. If resources were available, farmers would prioritize using seeds resistant to drought. In reaction to the dry prediction, farmers intended to mulch their fields to minimize evaporation losses. Since mulching is done by hand, it takes more physical capital than money. Little information is available regarding mulching, drought-tolerant seeds, or farmers' underutilization of climate forecasts when making crucial crop-management choices (Andersson et al. 2020).

Assuming resources were available, the second most important action was early plowing. However, less resource availability was a serious obstacle to action. The farmers had no access to any plowing subsidies (Wilk et al. 2017). The price, accessibility, and arrangement of tractors and plowing equipment frequently bring on delays. A small percentage of expenditures are occasionally covered by government subsidies (Wilk et al. 2017), and some farmers in both communities claimed to be unaware of the program. Few studies have been conducted on drought-tolerant crops, mulching, or the underutilization of climate forecasts by farmers when making crucial management decisions for their farms. Prediction uncertainty makes it more challenging to communicate seasonal climate forecasts to users, who generally find probability forecasts challenging to understand (Coventry & Dalgleish 2014; An-Vo et al. 2019). Studies also elicited that farmers made decisions without much consideration for scientific forecasts (Gilles & Valdivia 2009; Haigh et al. 2018).

The review demonstrates that older people desire interactive climate information because they are more susceptible to the effects of climate change. It can be presumed that farmers are more reliant on the extension agent, social groups, and neighbors because of their poor literacy, limited internet access, and limited capacity to interpret information obtained through ICT channels. Studies on how differently men and women access climatic information vary in contrast to age. Studies elicit that women and men have equal access to climate information, but in other studies, there are differences in how men and women choose to get the information, use it, and absorb it. Women rely on unofficial routes, but men have greater access to ICT channels. Similarly, educated people accept new technologies more readily than illiterate people and have greater access to ICT channels. Larger farmers are more likely to use the information, while smaller farmers are marginalized and unable to obtain climate information because of limited resources.

Research also shows that farmers' decision-making objectives are influenced by their mindset, knowledge, and culture. Farmers' decision-making objectives are contingent upon how information is transferred to them (frequency, range, and format). How often it is issued determines the forecast application. Most studies indicate that forecasts are released every month, with daily and seasonal climate forecasts with a three-month view following. Most studies offer the CIS as a forecast, but farmers are unaware of its use. Research has shown that farmers require advice on fertilizer application, irrigation, and seed variety.

However, few studies have shown that farmers rely on their expertise rather than consulting advisors or making recommendations. In most studies, farmers get or seek advice on extreme disasters, such as drought followed by flood. If we look at the decision-theoretic methodological processes, then cost/loss, farmers' willingness to pay, and net returns are used to leverage the value of CIS. Research projects the yearly gain and rise in profit margin from climate projections. Research indicates that farmers are more receptive to collaborative decision-making and are prepared to pay for agrometeorological and seasonal forecasts. Studies also used comparative analysis to demonstrate that farmers who use the estimates and recommendations had higher yields than those who do not. The type of year (heavy or dry) and the various stages of crop growth at which farmers receive the forecast also affect the increase and decrease in production.

Additionally, research has shown that short- and medium-term forecasts have more significant economic impact. When we consider the application of forecasts and changes in tactics, it is evident that farmers reported changes in strategies in most of the research, while few studies indicated no change in action. Most studies found that crop variety and crop mix changed, planting dates, crop acreage, and crops planted changed, and drought-tolerant seeds were planted. Other changes included increasing fertilizer, mulching, field modifications, chemical and chemical application changes, water harvesting, early plowing, purchasing additional livestock feed, preparing land for planting, adjusting irrigation, changing pest control techniques, managing soil and water resources, pre-employing labor, switching to agroforestry and intercropping, and selecting crops for diversification. The research revealed that many farmers mistakenly believe that seasonal and short-term forecasts are the same. This is because different research has shown varying ranges for defining short-term forecasts. The assessment also reveals that farmers favored short-duration crops during droughts or periods of low rainfall, and they would like additional information on precipitation forecasts for various agricultural cycle phases. Articles that detailed farmers' on-farm adaptations to the effects of climate change are included in the first theme. The articles pertaining to the second theme aimed to investigate possible approaches that farmers could employ to enhance their ability to adjust to the risks associated with climate change. These articles used modeling methodologies or opinion-based data to identify solutions that could be helpful for farmers rather than listing the acts that farmers are currently implementing. The main goals of these articles were to identify adaptation actions rather than analyze adaptation alternatives.

Even though many studies looked at farmers' adaptation from different angles, there was not a comprehensive grasp of the adaptation research activities. Results revealed that after 2010, most studies on farmers' responses to climate change were published. This surge and increased interest in climate adaptation can be attributed, in large part, to the developed world's 2009 increase in climate funding commitment. Regarding the geographic scope addressed, the assessed studies demonstrated a range of adaptation strategies in Africa and developed nations, with Asian nations coming next. The main objective of this study is to summarize the current research trends in the literature on farmers and how the characteristics of their farms influence decisions. Second, what format is the forecast given to the farmers? Third, what is the expected ‘value’ for the farmers? Fourth, how have adaptation practices included CIS? Studies also reveal that farmers' cultural backgrounds, information bases, and thought processes influence their decision-making. The review indicates that farmers rely more on extension agents, social groups, and neighbors because of their low literacy, restricted internet access, and poor interpretation of information acquired through ICT channels. Disparities in gender-specific climate information availability based on age have been examined in various ways. Similarly, educated individuals and larger farms are more likely to utilize this information. The forecast application is determined by the frequency, scope, and presentation of its releases. Most studies reported that monthly climate forecasts are issued, and over the next three months, daily and seasonal forecasts are published afterward. According to a survey, farmers need guidance on crop selection, irrigation, and fertilizer use. When significant disasters occur, such as droughts followed by floods, farmers usually seek guidance or receive it. Decision-theoretic methodological processes state that cost/loss, farmers' willingness to pay, and net returns can all raise the value of CIS. Higher yields were achieved by farmers who adhered to the forecast and recommendations than by those who did not. The kind of year (heavy or dry) and the various stages of crop growth at which farmers get the forecast also impact variations in production. Additionally, research has shown that short- and medium-term forecasts are important economically. For this study on agricultural adaptation, three main topics emerged from a systematic review: (i) documenting adjustments made on farms, (ii) adaptation options and CIS application, and (iii) challenges of adaptations.

Analyzing how adjustments made on farms and by farmers modify their tactics reveals that most research documents farmers modifying their methods, with very few studies documenting no change in practice. Most studies found that planting dates, crop acreage, crop variety, crop mix, and drought-tolerant seeds varied. Studies examining CIS applications and adaption options revealed that farmers frequently and strategically modify their management plans in response to the information they believe is relevant to the possibility of the upcoming harvest. Farmers gain from forecasts considering agricultural investment, crop choice, and farm operation scheduling. To reduce crop failure rates, increase farm productivity, and ensure that resources are used efficiently in agroecosystems, Nyantakyi-Frimpong (2019) asserts that CIS is critical. Decision-making was aided by greater availability of early warning systems, predictions, and guidance on drought resilience. Studies emphasized that climate-change-related rising temperatures and changed rainfall patterns can be lessened by timely irrigation, and accurate weather-based agro-advisory communications can lower the cost of irrigation pesticides and fertilizer. Rather than defining specific crop-specific adaptation strategies, they talked about strategies for adjusting to one crop or a mix of crops.

There was limited research on specific risk factors, circumstances, and vulnerabilities where specific adaptation methods changed. While this study draws attention to several issues, it also emphasizes the importance of on-farm adaptation strategies and the associated challenges. While making crucial crop management decisions, there is a dearth of research on mulching, drought-tolerant seed, or farmers' underutilization of conservation factors. Farmers did not plant drought-tolerant seeds despite the availability of information on seasonal climate forecast prediction since these seeds must be purchased. The cost, availability, and configuration of tractors and plowing equipment sometimes cause delays. Users generally find probability forecasts challenging to understand, and seasonal climate forecasts are more difficult to express due to prediction uncertainty. Most farmers, if not all, employ greater reactive rather than anticipatory adaptation techniques, while certain farms employ different techniques. This could happen because of their perspective on climate change. This analysis has shown that more research has been done on investigating possible adaptations or assessing the relative performance of adaptations to other themes.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

All relevant data are included in the paper or its Supplementary Information.

The author declares there is no conflict.